move tests to nightly (#4451)

* move tests to nightly

* clean up code quality issues

* more clean up

tests/pipelines/altdiffusion/test_alt_diffusion.py

@@ -25,7 +25,7 @@ from diffusers.pipelines.alt_diffusion.modeling_roberta_series import (
     RobertaSeriesConfig,
     RobertaSeriesModelWithTransformation,
 )
-from diffusers.utils import slow, torch_device
+from diffusers.utils import nightly, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
 
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
@@ -205,7 +205,7 @@ class AltDiffusionPipelineFastTests(
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
 
 
-@slow
+@nightly
 @require_torch_gpu
 class AltDiffusionPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):

tests/pipelines/altdiffusion/test_alt_diffusion_img2img.py

@@ -32,7 +32,7 @@ from diffusers.pipelines.alt_diffusion.modeling_roberta_series import (
     RobertaSeriesConfig,
     RobertaSeriesModelWithTransformation,
 )
-from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
+from diffusers.utils import floats_tensor, load_image, load_numpy, nightly, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
 
 
@@ -254,7 +254,7 @@ class AltDiffusionImg2ImgPipelineFastTests(unittest.TestCase):
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
 
 
-@slow
+@nightly
 @require_torch_gpu
 class AltDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):

tests/pipelines/audio_diffusion/test_audio_diffusion.py

@@ -29,7 +29,7 @@ from diffusers import (
     UNet2DConditionModel,
     UNet2DModel,
 )
-from diffusers.utils import slow, torch_device
+from diffusers.utils import nightly, slow, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
 
 
@@ -175,7 +175,7 @@ class PipelineFastTests(unittest.TestCase):
         assert np.abs(image_slice.flatten() - expected_slice).max() == 0
 
 
-@slow
+@nightly
 @require_torch_gpu
 class PipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):

tests/pipelines/consistency_models/test_consistency_models.py

@@ -10,7 +10,7 @@ from diffusers import (
     ConsistencyModelPipeline,
     UNet2DModel,
 )
-from diffusers.utils import randn_tensor, slow, torch_device
+from diffusers.utils import nightly, randn_tensor, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_2, require_torch_gpu
 
 from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GENERATION_PARAMS
@@ -161,7 +161,7 @@ class ConsistencyModelPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
 
 
-@slow
+@nightly
 @require_torch_gpu
 class ConsistencyModelPipelineSlowTests(unittest.TestCase):
     def tearDown(self):

tests/pipelines/dance_diffusion/test_dance_diffusion.py

@@ -20,7 +20,7 @@ import numpy as np
 import torch
 
 from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNet1DModel
-from diffusers.utils import slow, torch_device
+from diffusers.utils import nightly, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
 
 from ..pipeline_params import UNCONDITIONAL_AUDIO_GENERATION_BATCH_PARAMS, UNCONDITIONAL_AUDIO_GENERATION_PARAMS
@@ -116,7 +116,7 @@ class DanceDiffusionPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         super().test_inference_batch_single_identical(expected_max_diff=3e-3)
 
 
-@slow
+@nightly
 @require_torch_gpu
 class PipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):

tests/pipelines/dit/test_dit.py

@@ -20,7 +20,7 @@ import numpy as np
 import torch
 
 from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, Transformer2DModel
-from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
+from diffusers.utils import is_xformers_available, load_numpy, nightly, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
 
 from ..pipeline_params import (
@@ -106,8 +106,8 @@ class DiTPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3)
 
 
+@nightly
 @require_torch_gpu
-@slow
 class DiTPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):
         super().tearDown()

tests/pipelines/karras_ve/test_karras_ve.py

@@ -19,7 +19,7 @@ import numpy as np
 import torch
 
 from diffusers import KarrasVePipeline, KarrasVeScheduler, UNet2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
+from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch, torch_device
 
 
 enable_full_determinism()
@@ -64,7 +64,7 @@ class KarrasVePipelineFastTests(unittest.TestCase):
         assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
 
 
-@slow
+@nightly
 @require_torch
 class KarrasVePipelineIntegrationTests(unittest.TestCase):
     def test_inference(self):

tests/pipelines/paint_by_example/test_paint_by_example.py

@@ -24,7 +24,7 @@ from transformers import CLIPImageProcessor, CLIPVisionConfig
 
 from diffusers import AutoencoderKL, PaintByExamplePipeline, PNDMScheduler, UNet2DConditionModel
 from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
-from diffusers.utils import floats_tensor, load_image, slow, torch_device
+from diffusers.utils import floats_tensor, load_image, nightly, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
 
 from ..pipeline_params import IMAGE_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS, IMAGE_GUIDED_IMAGE_INPAINTING_PARAMS
@@ -165,7 +165,7 @@ class PaintByExamplePipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         super().test_inference_batch_single_identical(expected_max_diff=3e-3)
 
 
-@slow
+@nightly
 @require_torch_gpu
 class PaintByExamplePipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):

tests/pipelines/pndm/test_pndm.py

@@ -19,7 +19,7 @@ import numpy as np
 import torch
 
 from diffusers import PNDMPipeline, PNDMScheduler, UNet2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
+from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch, torch_device
 
 
 enable_full_determinism()
@@ -64,7 +64,7 @@ class PNDMPipelineFastTests(unittest.TestCase):
         assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
 
 
-@slow
+@nightly
 @require_torch
 class PNDMPipelineIntegrationTests(unittest.TestCase):
     def test_inference_cifar10(self):

tests/pipelines/score_sde_ve/test_score_sde_ve.py

@@ -19,7 +19,7 @@ import numpy as np
 import torch
 
 from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNet2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
+from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch, torch_device
 
 
 enable_full_determinism()
@@ -66,7 +66,7 @@ class ScoreSdeVeipelineFastTests(unittest.TestCase):
         assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
 
 
-@slow
+@nightly
 @require_torch
 class ScoreSdeVePipelineIntegrationTests(unittest.TestCase):
     def test_inference(self):

tests/pipelines/spectrogram_diffusion/test_spectrogram_diffusion.py

@@ -21,7 +21,7 @@ import torch
 
 from diffusers import DDPMScheduler, MidiProcessor, SpectrogramDiffusionPipeline
 from diffusers.pipelines.spectrogram_diffusion import SpectrogramContEncoder, SpectrogramNotesEncoder, T5FilmDecoder
-from diffusers.utils import require_torch_gpu, skip_mps, slow, torch_device
+from diffusers.utils import nightly, require_torch_gpu, skip_mps, torch_device
 from diffusers.utils.testing_utils import enable_full_determinism, require_note_seq, require_onnxruntime
 
 from ..pipeline_params import TOKENS_TO_AUDIO_GENERATION_BATCH_PARAMS, TOKENS_TO_AUDIO_GENERATION_PARAMS
@@ -162,7 +162,7 @@ class SpectrogramDiffusionPipelineFastTests(PipelineTesterMixin, unittest.TestCa
         return super().test_progress_bar()
 
 
-@slow
+@nightly
 @require_torch_gpu
 @require_onnxruntime
 @require_note_seq

tests/pipelines/versatile_diffusion/test_versatile_diffusion_image_variation.py

@@ -19,7 +19,7 @@ import numpy as np
 import torch
 
 from diffusers import VersatileDiffusionImageVariationPipeline
-from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
+from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
 
 
 torch.backends.cuda.matmul.allow_tf32 = False
@@ -29,7 +29,7 @@ class VersatileDiffusionImageVariationPipelineFastTests(unittest.TestCase):
     pass
 
 
-@slow
+@nightly
 @require_torch_gpu
 class VersatileDiffusionImageVariationPipelineIntegrationTests(unittest.TestCase):
     def test_inference_image_variations(self):

tests/pipelines/vq_diffusion/test_vq_diffusion.py

@@ -22,7 +22,7 @@ from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
 from diffusers import Transformer2DModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
 from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings
-from diffusers.utils import load_numpy, slow, torch_device
+from diffusers.utils import load_numpy, nightly, torch_device
 from diffusers.utils.testing_utils import require_torch_gpu
 
 
@@ -193,7 +193,7 @@ class VQDiffusionPipelineFastTests(unittest.TestCase):
         assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
 
 
-@slow
+@nightly
 @require_torch_gpu
 class VQDiffusionPipelineIntegrationTests(unittest.TestCase):
     def tearDown(self):